pertension.Purpose of the study. To determine the influence of air temperature, atmospheric pressure, precipitation, fast weather changes on the number of emergency calls to patients with heart disease in the cities of Bishkek and Osh.The data of calls to the ambulance station of the cities of Bishkek and Osh for a 20-year period (1998-2018) were analyzed by classes of diseases in accordance with the ICD 10revision A00-R99 - from all causes; I00-I99 - diseases of the circulatory system. More than 450 thousand ambulance calls were analyzed. To assess the meteorological indicators, the archived data of the site https//www.gismeteo.ru/diary/5327 were used. Correlation analysis was performed using the SPSS program.
The data of calls to the ambulance station of the cities of Bishkek and Osh for a 20-year period (1998-2018) were analyzed by classes of diseases in accordance with the ICD 10th revision A00-R99 - from all causes; I00-I99 - diseases of the circulatory system. More than 450 thousand ambulance calls were analyzed. To assess the meteorological indicators, the archived data of the site https//www.gismeteo.ru/diary/5327 were used. Correlation analysis was performed using the SPSS program.Results and conclusion. The data obtained indicate the presence of moderate and strong statistically significant relationships in the number of patients with cardiovascular diseases seeking medical care with periods of prolonged heat, days with a fast weather change, days with increased atmospheric pressure after the invasion of the cold air front and precipitation. The necessity of seasonal prophylaxis of meteopathic reactions taking into account weather changes is shown.Development of medical rehabilitation technologies are the investments into ?human capital?. https://www.selleckchem.com/btk.html The effectiveness criterion of the scientific institutions work dealing with the problems of rehabilitation is the scientific publication activity of their employees in this subject in high-ranking international databases (DB).Purpose of the study. Analysis of the state of the scientific publication flow in the field of rehabilitation.Data from the Web of Science and Scopus databases for November 2019, depth from 1991 to 2018 were used.
It was revealed that the high level of the publication rating of Russia, which was noted in 1991-1992, has not yet been achieved in the Scopus database for medical rehabilitation. Measures have been identified to enhance it by increasing the growth rate of the Russian publication flow. It also noted the necessity to reduce Russia's dependence on the monopoly of foreign publishing corporations by creating domestic Russian resources and borrowing the experience of foreign colleagues.easures should be taken at the level of authors, scientific organizations, the scientific community and the State in order to increase the Russian scientific publication flow in the direction of ?Rehabilitation? in foreign top-rated databases. Authors of interdisciplinary articles need to correctly present metadata indicating the relation of the work to the problem of rehabilitation. The necessity is substantiated not only to increase the share of Russian scientific journals in international databases, but also to create domestic high-rating databases, as well as to harmonize the existing regulatory legal acts in regards of terms and definitions in the field of rehabilitation, to bring the headings of the Universal Decimal Classification aligned with the headings of high-ranking international databases. Given the high social significance of the ?Rehabilitation? area, it is necessary to include it in the priority list and funded areas at a level corresponding to global trends.The novel Coronavirus Disease 2019 (COVID-19) infection broken out in Wuhan. We aimed to analyse the impact of medical support and population emigration from Wuhan on the cure rate and mortality of COVID-19 infection in China and to provide early warning on the developmental trend of the epidemic.
Data were obtained from The National Health Commission of People's Republic of China, Chinese Center for Disease Control and Prevention and The National Health Commission of People's Republic of Hubei Province. The Poisson distribution and normal approximate were used to analyse the relationship between population emigration from Wuhan and the probability of outbreaks and to predict the developmental trend of the epidemic situation.
The outbreak were related to population emigration from Wuhan in 87% of the cities in Hubei. The result of developmental trend indicated that 95% confidence intervals of confirmed case in Xiaogan and HuangGang were 3301.678-3526.042 and 3201.189-3422.17, respectively. For province outside of Hubei, the outbreak in 76% of the provinces were related to population emigration from Wuhan. Hot spot provinces for epidemic prevention included GuangDong and HeNan. Medical support significantly improved the cure rate of patients with COVID-19 (= 0.852, &lt; 0.001).
Population emigration from Wuhan has a certain impact on the probability of outbreaks COVID-19 in Hubei and the whole country, medical support improved the cure rate of patients with COVID-19.
Population emigration from Wuhan has a certain impact on the probability of outbreaks COVID-19 in Hubei and the whole country, medical support improved the cure rate of patients with COVID-19.This manuscript brings attention to inaccurate epidemiological concepts that emerged during the COVID-19 pandemic. In social media and scientific journals, some wrong references were given to a "normal epidemic curve" and also to a "log-normal curve/distribution". For many years, textbooks and courses of reputable institutions and scientific journals have disseminated misleading concepts. For example, calling histogram to plots of epidemic curves or using epidemic data to introduce the concept of a Gaussian distribution, ignoring its temporal indexing. Although an epidemic curve may look like a Gaussian curve and be eventually modelled by a Gauss function, it is not a normal distribution or a log-normal, as some authors claim. A pandemic produces highly-complex data and to tackle it effectively statistical and mathematical modelling need to go beyond the "one-size-fits-all solution". Classical textbooks need to be updated since pandemics happen and epidemiology needs to provide reliable information to policy recommendations and actions.